[EN] Big Tech, AI Regulation, and the Future of the Market
1. The "AI Copyright Act" and
Tech Giants
Explain the legal challenges companies like
OpenAI, Microsoft, and Adobe are facing regarding AI training data.
- Key Point: Why the "Fair
Use" doctrine is being tested in the age of generative AI.
2. Regulation as a New Market Barrier
Interestingly, strict regulations can
sometimes benefit "Big Tech" (the incumbents) by creating high entry
barriers for smaller startups.
- Insight: How "Regulatory
Capture" might influence the AI industry's hierarchy in 2026.
3. Investment Takeaway: Infrastructure
vs. Content
While laws are being debated, the
"Picks and Shovels" (Nvidia, TSMC) remain safe, but content owners
(Disney, Getty Images) are the new "Dark Horses" in the AI era.
4. Bbiri’s Insight: The Cost of Fair Compensation and the Risk of a New Digital Divide
At the intersection of law and technology,
I believe we are entering an era of 'Fair Compensation.' As the days of
unauthorized AI training come to an end and licensing agreements become
mandatory, our focus must shift. We need to pay closer attention to who owns
the 'rights' to feed the algorithms, rather than just the algorithms
themselves.
However, there is a critical risk to
consider as licensing becomes a necessity: the potential for AI tools to
become detached from reality. Some AI companies may rush to launch tools
without securing sufficient licenses. If this trend continues, we may see a
society where information gaps widen based on income levels, much like
in the past.
Such a shift would be a negative societal
change. To prevent this, we must remain vigilant and work toward solutions that
ensure AI development does not leave anyone behind in a new era of digital
inequality.
What are your thoughts on the future of AI and information equality? Let’s discuss in the comments!
⚠️ Investment Disclaimer:
- The content on this blog is for informational and educational purposes only and does not constitute financial, investment, or professional advice.
- Investing in the stock market involves significant risk, and past performance is not indicative of future results.
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